Breast cancer is the most frequently diagnosed cancer in women in the United States and Europe, with an estimated 608,380 new cases of invasive disease in 2007 (REFS 1,2). Despite a recent decrease in breast cancer inci-dence rates in the United States3, it remains the second leading cause of cancer deaths in American women. Our current understanding of the biology of breast cancer is a major barrier to identifying novel therapies and improv-ing existing therapies for the treatment and prevention of this disease.

Breast cancer is not a single disease. It is instead a col-lection of breast diseases that have diverse histopatholo-gies, genetic and genomic variations, and clinical outcomes (FIG. 1). A major challenge in advancing our understanding of the biology of breast cancer is the avail-ability of experimental model systems that recapitulate the many forms of this disease. Because of this complexity and heterogeneity no single model would be expected to mimic all aspects of the disease. Thus, when investigating breast cancer there are several key questions. How do we optimally use the existing models? What issues affect the development of new models? And, how do we improve preclinical models to evaluate potential new therapies? For breast cancer and most other solid cancers, it will be necessary to develop models to evaluate treatments for metastatic disease and to enhance our understand-ing of the mechanisms that underlie metastatic pro-gression, which is the principal cause of mortality. This represents one of the foremost challenges for breast cancer researchers.

Here, we highlight the strengths and limitations of the existing experimental models used to investigate the multistage process of breast cancer initiation and pro-gression. These include human breast cancer cell lines, xenografts and genetically engineered mice (GEM).

We discuss how well cell lines model this complex dis-ease in two-dimensional (2D) and three-dimensional (3D) cultures and as xenografts. We also describe advances in generating xenografts of primary breast cancers. Finally, we illustrate how GEM collectively demonstrate an emerging principle of breast cancer biology; the initiating oncogene(s), cell of origin and developmental timing of oncogenesis act in concert to dictate tumour initiation and progression. Although GEM cannot completely recapitulate all aspects of breast cancer, they are especially valuable for elucidat-ing the mechanisms that regulate the initiation and progression of this disease. We conclude that using an integrated and multi-systems approach is the most powerful way to model this heterogeneous disease.

Breast cancer cell linesBreast cancer cell lines have been the most widely used models to investigate how proliferation, apoptosis and migration become deregulated during the progression of breast cancer4. The use of cell lines has resulted in a wealth of information about the genes and signalling pathways that regulate these processes. There are numerous rea-sons why human breast cancer cell lines have been the principal models for breast cancer research. Established cell lines are easily propagated, relatively tractable to genetic manipulation and, under well-defined experi-mental conditions, generally yield reproducible and quantifiable results.

Compared to rodent cells, human cells are frequently perceived as having more ‘relevance to human disease’ owing to the fundamental differences between organ-isms. Furthermore, there is an ongoing debate as to whether the same genetic alterations transform both mouse and human epithelial cells5–7. It is also apparent

Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA. Correspondence to J.M.R. e‑mail: jrosen@bcm.edudoi:10.1038/nrc2193

Modelling breast cancer: one size does not fit allTracy Vargo‑Gogola and Jeffrey M. Rosen

Abstract | Breast cancer is not a single disease, but is instead a collection of diseases that have distinct histopathological features, genetic and genomic variability, and diverse prognostic outcomes. Thus, no individual model would be expected to completely recapitulate this complex disease. Here, the models commonly used to investigate breast cancer including cell lines, xenografts and genetically engineered mice, are discussed to help address the question: what is the most powerful way to investigate this heterogeneous disease?

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 659

© 2007 Nature Publishing Group

Triple negative subtypeA subtype of invasive ductal carcinoma that is ER, PR and ERBB2 negative.

Pleural effusionA fluid, which contains tumour cells, that accumulates between the thin layers of tissue lining the lung and  chest wall.

that some aspects of breast cancer, particularly steroid hormone dependence, are not well modelled in mice8, whereas several breast cancer cell lines exhibit hormone dependence, allowing the investigation of oestrogen and progesterone-regulated signalling pathways in breast cancer. Finally, cell lines can be grown as xenografts, allowing the examination of the effects of altered gene function and chemical inhibition of signalling path-ways on the tumorigenicity of the cells both in vitro and in vivo. However, multiple variants of the same cell line exist throughout the scientific community, and many of these display distinct phenotypes, which indicates that they have acquired genetic changes that might preclude comparison between different studies9. Such caveats need to be considered when using cell lines.

Are cell lines representative of human breast cancer? This has recently been investigated by comparing the gene-expression profiles and genomic alterations of multiple breast cancer cell lines and primary breast cancers10–13. As expected, these studies indicate that no single cell line is truly representative; however, a panel of cell lines shows the heterogeneity that is observed in primary breast cancers. The most comprehensive of these studies, reported by Gray and colleagues13, demonstrated that a panel of 51 breast cancer cell lines shows many of the recurrent genomic abnormalities that are detected in pri-mary tumours. Thus, the establishment of these tumours as cultured cell lines did not markedly alter the common genomic aberrations. However, important differences were detected in the cell lines compared to the primary tumours. For example, primary luminal and basal sub-type tumours showed pronounced differences in the fre-quency of genome copy number abnormalities (CnAs). By contrast, the luminal and basal cell lines show similar levels of CnAs, suggesting that their establishment and

propagation in culture has selected for a certain degree of genomic alteration. Additionally, not all of the five common subtypes of ductal carcinoma, which includes luminal A, luminal B, basal, ErBB2+ and triple negative subtypes (FIG. 2), were represented. Most notably, separate luminal subtypes were not distinguished, and neve et al.6 described distinct basal A and B subtypes that were not identified in other studies. These investigators, therefore, refer to the classification of the cell lines into luminal and basal subtypes as “aspects of cancer biology [that] are more or less accurately represented by the cell line system,” which is clearly a cautionary note that needs to be considered when using these cell lines to investigate breast cancer.

The differences between the cell lines and primary tumours probably reflect that many of the cell lines were obtained from advanced-stage tumours and pleural effu-sions, and, therefore, may represent the most malignant variants that could be adapted to culture. However, there is evidence that gene-expression profiles of pri-mary tumours and their metastatic counterparts are not markedly different10,14,15. With the application of molecular profiling to identify the unique subtypes and the improved methods for immortalizing and culturing human breast cells6,16, it should be possible to establish new cell lines from primary tumours and different breast cell lineages17. These new cell lines may be more representative, and thus may expand the utility of cell culture models.

Do cell lines contain tumour-initiating cells? A seminal study demonstrated that a limited number of breast cancer pleural effusions contains a small subpopulation of tumour-initiating cells18. The identification of cell-surface markers, CD44+CD24– and epithelial surface antigen (ESA)+, has allowed the isolation and characteri-zation of these cells18,19. These cells undergo self-renewal in mammosphere assays (FIG. 3c), and when transplanted as xenografts (FIG. 3d) give rise to tumours that contain the differentiated cell types present within the original tumours18,19. Tumour-initiating cells are proposed to be more resistant to therapy and lead to disease recurrence and metastasis; evidence is accumulating to support this hypothesis20–23.

To develop therapies that target tumour-initiating cells it is critical to understand their biology and to determine whether breast cancer subtypes contain similar or distinct types of tumour-initiating cells. Despite recent advances in propagating primary breast cancers as xenografts using a humanized fat pad in immunocompromised mice24 and in non-adherent mammosphere cultures16,19,25, it remains a significant challenge to perpetuate and expand cells and tissues from primary clinical isolates. Thus, the potential application of breast cancer cell lines to investigate the biology of tumour-initiating cells provides an attractive alternative.

A key issue is whether breast cancer cell lines contain tumour-initiating subpopulations. A few laboratories have identified subpopulations within cell lines that have distinct tumour-initiating phenotypes. For example, an

At a glance

• The models commonly used to investigate breast cancer, including breast cancer cell lines, xenografts and genetically engineered mice (GEM), are discussed. Their strengths and limitations, and how they can be optimally used and improved, are described.

• Breast cancer cell lines share many of the genetic and genomic features of human breast cancers, including representing several breast cancer subtypes. Several cell lines may also serve as models to investigate tumour-initiating cell properties.

• Utilization of cell lines as subtype systems in three-dimensional and heterotypic cultures represent powerful approaches to investigate the signalling interactions that contribute to breast cancer biology.

• Xenografts of cell lines and breast cancer clinical isolates allow for the examination of human breast cancer cells in the context of the in vivo environment, as the cell culture environment cannot completely recapitulate the complex multicellular and cell–extracellular matrix interactions that are involved in the initiation and progression of breast cancer.

• Genetically engineered mouse models of breast cancer exhibit many features of human breast cancer and thus provide invaluable models for investigating the biology and pathogenesis of this disease. The accumulating number of molecular profiling studies provide a framework for comparing GEM and human breast cancer.

• Because of the complexity and heterogeneity of breast cancer no individual model recapitulates all aspects of this disease. Thus, an integrated and multi-systems approach is currently the strongest way to model this disease.

R E V I E W S

660 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

Genomic instability

Normal Premalignant Malignant

Increasing risk: × 4–6 × 10–12

Nature Reviews | Cancer

Epigenetic

TDLU ADH IBC METDCIS

Fibroblast

Luminal epithelial cell

Myoepithelial cell

Macrophage

Extracellular matrix

Epigenetic and genetic changes

Basement membrane

Tumour cells

Intravasation

Lung parenchymaExtravasation

Activated stroma

a

b

c

Self-renewal

Blood vesselTumour–stromal cell interactions

Luminal epithelial cells

Luminal progenitor

LT ST

Differentiation

Mixed lineage tumour

Luminal lineage tumour

Basal lineage tumour

Myoepithelial cells

Myoepithelial progenitor

Metastatic tumour growth

Figure 1 |Thebiologyofbreastcancer.a | Breast cancer is a genetically and genomically heterogeneous disease that develops along a continuum. The normal breast terminal ductal lobular unit (TDLU) contains lobules and ducts that consist of a bi-layered epithelium of luminal and myoepithelial cells. Atypical ductal hyperplasia (ADH) is a premalignant lesion characterized by abnormal cell layers within the duct or lobule. ADH is thought to be the precursor of ductal carcinoma in situ (DCIS), which is a non-invasive lesion that contains abnormal cells. With each stage, the risk of developing malignant or invasive breast cancer (IBC) increases. DCIS may give rise to IBC (indicated by a blue star adjacent to a DCIS lesion), but it is unclear how to predict which lesions will progress. Once cells have invaded, the risk for developing metastasis significantly increases. The lymph nodes are the primary site for breast cancer metastasis (MET; indicated by a blue star). b | A schematic of breast cancer progression is shown. The transformation of breast epithelial cells to give rise to metastatic breast cancer is an amalgamation of epigenetic and genetic changes and aberrant interactions within the microenvironment. During this multistage process, control of proliferation, survival, differentiation and migration become deregulated, and aberrant tumour– stromal cell interactions facilitate this process. To form metastases, cells must invade through the basement membrane, enter the vasculature (intravasate), survive in the absence of adhesion, exit the vasculature (extravasate) and establish a new tumour in a foreign microenvironment14,60,129. c | Several parallels between normal breast stem or progenitor cells and cancer cells, such as dormancy, self-renewal and differentiation capabilities, have lead researchers to propose that cancer cells with stem cell-like characteristics (called ‘cancer stem cells’ or ‘tumour-initiating cells’, which is a more appropriate designation), drive breast cancer initiation, progression and recurrence130. This hypothesis is depicted as epigenetic and genetic alterations that occur in different stem or progenitor cells, including the long term (LT), short term (ST) and luminal or basal (myoepithelial) progenitors, and give rise to different subtypes of tumours that consist of different cell types (mixed, luminal or basal lineage), which display characteristic gene-expression profiles and exhibit distinct prognoses.

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 661

© 2007 Nature Publishing Group

Nature Reviews | Cancer

Luminalsubtype A

Luminalsubtype B

ERBB2+ Normalbreast-like

Basalsubtype

a

b

0.00 24 48 72 96

0.2

0.4

0.6

0.8

1.0

Overall survival (months)

Prob

ablit

y

Limiting dilution transplantationAn experimental method for estimating the number of cells that have stem or progenitor or tumour-initiating behaviour within a population of cells.

AldefluorAn aldehyde dehydrogenase (ALDH) substrate that allows the identification and isolation of stem or progenitor cells based on the observation that these cells have high ALDH activity.

MCF-7 sub-line, MCF-S, forms mammospheres, exhibits the CD44+CD24– expression profile and is enriched by 1000-fold in tumour-initiating capacity compared with the parental cells19. Other laboratories have examined subpopulations of MCF-7 cells that demonstrate reduced sensitivity to radiation and enhanced self-renewal capabilities in mammosphere assays26–28. However, the tumour-initiating capability of these subpopulations was not reported.

recently, Kuperwasser and colleagues tested the tumour-initiating potential of CD44+CD24– populations within breast cancer cell lines directly by performing limiting dilution transplantation experiments. These markers did not correlate with tumour-initiating capability, but instead were indicative of a basal subtype (C. Kuperwasser and C. Fillmore, personal communication). However, an ESA+ fraction within the CD44+CD24– subpopulation showed enrichment for tumour-initiating capability and increased resistance to chemotherapeutic agents.

Is the expression of CD44+CD24–ESA+ markers broadly indicative of tumour-initiating subpopulations within cell lines? Accumulating evidence suggests that their expression is heterogeneous within cell lines and breast cancers19,29–31. Furthermore, their relationship to clinical outcome is unclear30–32. More functional studies (using limiting dilution transplantation of cells isolated by FACS (fluorescent activated cell sorting)) that utilize the different subtypes of breast cancer are required to conclude definitively whether each subtype contains subpopulations of tumour-initiating cells and whether they display identical or distinct cell surface markers. Improved methods and markers are needed to identify and characterize tumour-initiating cells within cell lines and breast cancers. One promising approach may be to use the stem cell marker aldefluor33 in FACS analy-sis coupled with immunohistochemistry (IHC) using an anti-aldehyde dehydrogenase 1 (AlDH1) antibody (M. Wicha, personal communication). notwithstanding these limitations, several studies indicate that certain cell lines can be used to investigate the cellular and molecular distinctions between the tumour-initiating and non-tumour-initiating subpopulations19,26,28,34.

2D versus 3D culture conditions. The molecular profil-ing studies described above indicate that cell lines have many of the genetic and genomic alterations found in primary breast cancers. However, most of these studies were performed using cell lines cultured on plastic12,13,35. A principal limitation of in vitro cell culture studies is that the culture conditions used to propagate these cells create an environment that differs markedly from the breast microenvironment. This caveat must be consid-ered when discussing the fidelity with which cell lines model breast cancer (FIG. 3).

recently, to determine whether gene expression, like morphology, is more faithfully recapitulated in breast can-cer cell lines when grown in 3D reconstituted basement membrane (rBM) cultures, the molecular profiles of 25 breast cancer cell lines cultured in 2D versus 3D conditions were compared36. not surprisingly, molecular profiles of individual cell lines were more similar to themselves than to other cell lines grown in the same culture conditions, indicating that the 3D culture environment does not pro-mote global changes in gene-expression patterns. However, a group of signal transduction genes were identified that significantly correlated with cells grown in the 3D envi-ronment. Altered expression of these genes coupled with post-transcriptional gene regulation probably accounts for the morphological and behavioural differences of cells grown in 3D compared with 2D cultures37.

Bissell, Brugge and colleagues have pioneered the 3D culture methods of breast epithelial and tumour cell lines, and readers are directed to a number of excellent reviews on modelling the microenvironment in 3D cultures38–41. Three-dimensional culture models have been used to investigate the critical signalling pathways that regulate tumour biology. For example, Weaver and colleagues42 have demonstrated how one feature of breast cancer biology, stromal rigidity and its effects on morphogenesis, can be modelled in 3D cultures,

Figure 2 |Theidentificationofbreastcancersubtypesbymolecularprofiling.a | The concept that breast cancer is not a single disease is demonstrated by the increasing number of gene-expression profiling studies, which suggest that there are at least five subtypes of invasive ductal carcinoma (IDC) that constitute approximately 80% of all breast cancers10,131. A dendogram shows clustering of 115 breast tumours into the five subtypes of IDC. Grey branches indicate tumours that did not correlate with any subtype132. Invasive lobular carcinomas, which also display distinct gene-expression profiles, constitute an additional 10–15% of breast cancers (not shown)133. Ten additional rare types of breast cancer have also been described, although collectively these account for less than 10% of newly diagnosed cases each year (see the Mayo Clinic web page on breast cancer). b | The prognostic outcomes for each subtype of IDC are shown as overall survival. The ERBB2+ and basal subtypes demonstrate the worst prognoses, whereas the luminal subtype A shows the most favourable outcome. Recently, it has been demonstrated that the prognostic outcomes of the subtypes were not different when a pathologically complete response to therapy was achieved134. It has been suggested that the distinct prognostic outcomes between the subtypes may reflect the differential responses of the bulk of the tumour and tumour-initiating cell populations to chemotherapy and targeted therapies135. Reproduced with permission from REF. 132 (2007) National Academy of Sciences, USA.

R E V I E W S

662 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

Nature Reviews | Cancer

Subcutaneous xenograft

Injection into skin

Orthotopic xenograft

Mammary fat pad

Experimental metastasis

Tail vein injection

Immunocompromised mouse

Lymph node

a

b

c

d

Proliferation

Apoptosis3D rBM culture of normalbreast epithelial cells

Cells in monolayer ontissue culture plastic

Proliferation

3D rBM culture of breast cancer cells

Non-adherent mammosphere culture

Hollow lumen

ECM

Failure of epithelium topolarize, growth arrestand form lumen

Invasion

Polarized and growth-arrested epithelium

Stem or progenitor cellSelf-renewal of stem or progenitor cell

Progeny cell

Tumour cells

Matrix complianceThe flexibility of the matrix surrounding the cells, which exerts forces that affect cell behaviour.

HomotypicAn interaction between cells of the same type.

allowing the delineation of the signalling pathways that regulate these processes. These investigators mim-icked the stromal rigidity of breast tumours by reducing the matrix compliance, which was sufficient to promote tumour-like morphogenesis of normal mammary epithe-lial cells. This aberrant morphogenesis was regulated by rho-dependent cytoskeletal tension, growth factor, integrin and focal adhesion signalling interactions, and importantly, these pathways have been implicated in breast cancer43–45.

More recently, breast cancer cells grown in 3D culture were used to identify an autocrine loop dependent on epidermal growth factor receptor (EGFr), transforming growth factor-α (TGFα), amphiregulin and tumour-necrosis factor-α converting enzyme (TACE, also known as ADAM17), which promotes breast cancer cell prolif-eration and disrupts architecture46. Strikingly, expression levels of TACE and TGFα were highly correlated with poor prognosis in breast cancers, suggesting that these

molecules may have potential as therapeutic targets in EGFr-dependent breast cancers. Taken together, these studies demonstrate how 3D cultures can be used to mimic the in vivo tumour environment and to delineate critical signalling pathways that contribute to breast cancer.

Homotypic versus heterotypic cultures.  Another constraint of cell culture experiments is that they are usually homotypic and do not allow the examination of tumour–stromal cell interactions. During tumour growth the stroma evolves to establish paracrine interactions that facilitate tumour progression (FIG. 1). Thus, elucidating the mechanisms that regulate these interactions is critical and may yield new targets within the stromal environment for cancer therapy47,48. Crucially, it has been proposed that tumour stromal cells are genomically stable, and therefore are unlikely to acquire rapid resistance to therapy47, although this hypothesis is controversial49.

Figure 3 |culturemethodsandxenografts.Fundamental differences in the cell culture environment compared with the breast microenvironment affect cell behaviour136. a | Two-dimensional (2D) cultures grown on plastic lack exposure to components of the extracellular matrix that are present in vivo, are exposed to a non-physiological substratum, lack heterotypic cell–cell interactions and do not recapitulate three-dimensional (3D) tissue architecture136–138. b | The morphology and behaviour of non-transformed breast epithelial cells in 3D reconstituted basement membrane (rBM) cultures more accurately mimic breast structure and function136. Non-transformed breast epithelial cells grown in these conditions undergo a well-characterized morphogenesis process139. However, when breast cancer cells are grown in 3D cultures they fail to become growth arrested, lack polarity, display aberrant architectures and may become invasive39,136. Protocols are available to make the implementation of these methods achievable139. c | Mammosphere cultures, which are distinct from the morphogenesis assays that are performed on 3D rBM cultures, provide an assay for self-renewal of cells. A specific density and number of cells are plated in low-adherence plates within a defined medium. These conditions prevent differentiation and allow self-renewal of stem or progenitor cells. d | Xenograft tumours are produced by injecting tumour cells (0.5–5 × 106) into the flank (subcutaneous) or into the mammary fat pad (orthotopic) of immunocompromised mice. Tumour formation usually occurs rapidly and reproducibly, and large cohorts of tumour-bearing mice can be generated. Xenografts of hormone-dependent cell lines allow the examination of hormone regulation in breast cancer. For these reasons, xenografts are widely used as preclinical models (for a review see REF. 69). Xenografts have also been used extensively to investigate metastasis. In spontaneous metastasis assays, metastases arise from orthotopic tumours, and tumour cells must be competent in all steps of metastasis. In experimental metastasis assays, tumour cells are injected into the vasculature via intracardiac or intravenous injection140, bypassing some crucial steps of metastasis141. Not surprisingly, the relevance of experimental metastasis assays has been controversial142.

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 663

© 2007 Nature Publishing Group

Angiogenic switchA shift in the net balance between positive and negative angiogenesis factors in which there are increased positive factors to promote the growth of new blood vessels in tumours.

Breast cancer cell lines have been used to build heterotypic co-culture systems that allow the selec-tive examination of interactions between tumour and stromal cells, including macrophages, fibroblasts and endothelial cells. For example, co-cultures have been used to investigate the role of macrophages in promoting breast tumour cell invasion, and these experiments have allowed the delineation of the signalling pathways that mediate crosstalk between breast tumour cells and macrophages50–52. In these experiments, the phenotypes were dependent on the tumour–stromal cell interactions facilitated by the hetero-typic culture, highlighting the utility of this system. Strong correlations between macrophage infiltration in breast tumours and poor prognosis have been identified, demonstrating the relevance of these tumour–stromal cell interactions53,54. Therefore, the use of co-culture systems may provide new stromal targets to inhibit tumour progression. It is important to realize that modelling these interactions in culture is a significant challenge, and it has not yet been pos-sible using in vitro systems to model the complex mul-ticellular interactions that contribute to key aspects of breast cancer biology such as the angiogenic switch55. For these reasons, in vivo models remain critically important for investigating breast cancer.

Do xenografts mimic human breast cancer?The growth of breast cancer cell lines as xenografts allows investigation in the in vivo environment, which includes the complex tumour–stromal cell interactions that facilitate tumour formation and progression. Many facets of breast cancer biology have been investigated using xenografts, including the genetic alterations that contribute to tumour initiation and growth, the role of the microenvironment (tumour cell–extracellular matrix interactions, inflammation and angiogenesis), and the multistage process of metastasis56. However, there are sev-eral caveats to consider when using xenograft models.

A fundamental limitation of this approach is that it uses cell lines that may not represent the most common types of breast cancer observed in the clinic. There are also several technical aspects that affect the utility of xenograft models. First, xenografts must be established in immunocompromised mice, and the absence of an intact immune system may profoundly affect tumour development and progression57. In fact, there is increas-ing evidence of roles for the immune system in both early stage breast cancer and metastasis52,58. Xenografts are frequently generated by subcutaneous injection of the tumour cells into the flank of the mouse, and this microenvironment may alter the growth and metastatic potential of the engrafted cells (FIG. 3d). Orthotopic trans-plantation of cells into the mammary gland provides a more favourable microenvironment, although there are crucial differences in the mouse and human mammary stroma59. During the development of breast cancer in humans, the epithelial and stromal compartments co-evolve. By contrast, the introduction of tumour cell lines into the microenvironment of the mammary fat pad may not reproduce these complex interactions. Finally,

investigation of metastasis using xenografts and mouse models is problematic because metastatic cells prefer-entially colonize the lungs and usually fail to grow at other common sites that occur in human breast cancer, including the lymph nodes, liver, bone and brain60.

Are xenograft experiments relevant to human breast cancer? Massague and colleagues61 addressed this ques-tion in an elegant study in which MDA-MB-231 breast cancer cells were used in an intravenous experimental metastasis assay to select for increasingly metastatic vari-ants that preferentially metastasized to the lungs or bone. A metastasis gene signature was defined by molecular profiling the lung variants. Interestingly, a subset of these genes correlated significantly with decreased metastasis-free survival and specifically identified patients who relapsed with lung metastases, but not bone metas-tases. Other investigators have identified gene signa-tures using xenografts that correlate with prognostic outcome62,63. These exciting studies demonstrate the utility of xenograft assays and their direct relevance to human breast cancer.

Xenografts of breast cancer clinical isolates. The appli-cation of xenograft transplantation to perpetuate and expand breast cancer clinical isolates provides unique tools to investigate various aspects of breast cancer biology. For example, this technology has been used to investigate tumour-initiating properties and to identify critical signalling pathways, including BMI1 (a ring-finger polycomb group protein) and Hedgehog, that regulate the self-renewal of subpopulations derived from breast cancers18,64. However, these studies described results from a limited number of samples, and transplan-tation efficiencies were not reported. Chang, lewis and colleagues have recently demonstrated a 42% (14/33) transplantation efficiency of primary breast cancer xenografts (J. Chang and M.T. lewis, personal com-munication). Of these, however, only 2 tumours have demonstrated serial transplantation.

Although the utility of primary xenografts for inves-tigating tumour-initiating cell properties is evident, few laboratories are using this approach because it is inefficient and access to clinical samples is limited. The requirement of immunocompromised mice for transplantation is probably a key limitation affecting xenograft outgrowth as increasing evidence supports a role for the immune system in promoting tumour growth and progression65. Advances in the characterization and isolation of tumour-promoting immune cells, combined with methods for co-transplantation of these cells, may improve transplantation efficiencies.

Cell lines as preclinical models. Human breast cancer cell lines have been used extensively as preclinical models both in vitro and in vivo as xenografts. The ability of anticancer agents to inhibit cell proliferation in vitro is typically eval-uated as a measure of drug activity and has been shown to have clinical predictive value for breast cancer66. Can we improve the utility of cell lines as preclinical models? Gray and colleagues13 propose that when subtype cell lines are used as a ‘system’, rather than individually, they serve

R E V I E W S

664 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

Intravital microscopyFluorescence microscopy that allows the visualization of individual cells within living tissues or animals.

as powerful tools to investigate the signalling pathways that are associated with therapeutic response. For exam-ple, a subset of ErBB2+ cell lines that do not respond to anti-ErBB2 therapy were used to identify a gene-expression signature that is associated with therapeutic non-responsiveness. Thus, the cell line system may have particular use for elucidating the molecular mechanisms that underlie therapeutic response.

Although these data seem promising, more studies that use the subtype cell lines as a system, both in vitro and as xenografts, are required to prove that the subtype cell line system is better for testing breast cancer thera-peutics than other models. However, for breast cancer, the 51-cell line panel13 seems to have several advantages over the well-studied nCI60 panel of cancer cell lines, which contains only 7 breast cancer cell lines, most of which are the basal subtype67.

Therapeutic inhibition of breast cancer xenograft tumour growth has also been shown to predict activity in phase II clinical trials68. However, it is important to recognize that, in general, xenograft models have lim-ited use in predicting whether anticancer agents will be effective in treating human cancer66,69. The requirement for immunocompromised hosts, transplantation of human breast tumour cells into a foreign microenvi-ronment and a lack of co-evolvement of the epithelial and stromal compartments of the tumour are just a few of the many potential reasons why testing therapeutics in breast cancer xenograft models has fallen short of predicting efficacy in human breast and other types of cancer. Advances in humanizing the mouse mammary fat pad, including reconstituting tumour-promoting immune and fibroblast compartments, may improve xenograft models70,71. In addition, panels of subtype xenografts may be more predictive of drug activity than a single cell line xenograft model. Although these approaches may improve the use of xenografts as pre-clinical models, this is a particularly complex problem. A more in-depth understanding of the role of the immune system, microenvironment and the genetics

and biology of the different subtypes of breast cancer will be required before substantial strides can be made in improving xenografts as preclinical models.

GEM of breast cancerGEM have contributed extensively to our understand-ing of the genes that are involved in the promotion and progression of breast cancer. This includes examining the effects of the loss of tumour suppressor genes that are known to have significant roles in human breast cancer, including Trp53, Brca1 and Pten (phosphatase and tensin homologue), and the effects of gain of func-tion in oncogenes such as Erbb2, Myc, Ccnd1 (encoding cyclin D1), polyoma virus middle T (pyMT), and Hras. A wealth of information about the signalling interac-tions that contribute to tumour formation and progres-sion has been obtained by interbreeding various GEM that model breast cancer. The application of intravital microscopy in GEM has provided a window through which to view the processes that contribute to tumour progression, including angiogenesis, inflammation and the many steps of metastasis72,73. Therefore, GEM have provided invaluable tools for investigating the genetics and pathogenesis of breast cancer, and methods have been described recently for optimizing their utility as preclinical models69,74.

The first GEM of breast cancer were generated by targeting oncogenes such as Myc, pyMT, rat Erbb2 (also known as Neu) and Hras to the mammary gland using mouse mammary tumour virus long terminal repeat (MMTv-lTr) and whey acidic protein (Wap) promot-ers75–78. These relatively simple transgenic strategies provided tools to investigate how oncogenes and their interacting pathways contribute to breast tumorigenesis. However, there are several aspects to consider, particu-larly relating to these promoters, when discussing the utility of GEM as models for breast cancer (BOX 1).

Advances in genetic engineering have allowed more precise control of the developmental timing of loss or gain of gene function, tissue selectivity and targeting of

Box 1 | Features of the MMTV and Wap promoters

The MMTV (mouse mammary tumour virus) and Wap (whey acidic protein) promoters are hormonally regulated, and their expression in the mammary gland increases during pregnancy and peaks at lactation. These promoters are also expressed in the developing virgin mammary gland and potentially in the embryonic mammary bud80. The genomic integration site affects the expression levels of transgenes that are driven by these promoters, and thus individual transgenic lines created using the same construct may vary in their expression levels113. These promoters are mammary gland selective, but not specific. The MMTV promoter is expressed in the lungs, kidneys, salivary glands, seminal vesicles, T-cells, testes, prostate and potentially additional tissues depending on the integration site114,115. The Wap promoter is expressed at low levels in a variety of other tissues including the brain116. Thus, transgene expression may have systemic effects, which could potentially alter mammary gland development or tumorigenesis.

Mammary gland transplantation into wild-type hosts can be used to determine whether transgene effects are mammary epithelial cell autonomous117. These promoters usually result in transgene expression throughout the ductal tree118; this does not recapitulate the development of human breast cancer, in which oncogene expression or loss of tumour suppressor function occurs in a limited number of cells. Recently, a genetically engineered mouse model was developed that allows the targeting of oncogenes to a limited number of epithelial cells, which may better reflect the development of human breast cancer88. Another limitation of the MMTV and Wap promoters is that the level of oncogene expression that is driven by these promoters may not correspond to the expression level of the same oncogene in human breast cancer. Finally, these promoters may not target the cell types that are the cells of origin in human breast cancer. Although there are several caveats to consider when using these strategies, the use of the MMTV and Wap promoters to develop genetically engineered mouse models, has been instrumental in elucidating the genetics and biology of breast cancer.

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 665

© 2007 Nature Publishing Group

FibrosisThe formation of excess fibrous connective tissue that results from a reactive process within the tumour stroma.

particular cell types in GEM. These strategies include tetracycline (tet)-regulatable transgenes79, Cre/loxP recombinase-mediated somatic gene deletion or activa-tion driven by various promoters (for example, MMTv, Wap or keratin-14 (K14) promoters)80–83, inducible Cre recombinase (Wap-reverse tetracycline transactivator (rtTA))-Cre, Cre-oestrogen receptor tamoxifen-inducible (Cre-ErT), progesterone receptor (pr)-Cre, pr-bacterial artificial chromosome inducible Cre (pr-BACiCre))84–87, and in vivo retrovirally mediated delivery of transgenes via intraductal injection (replication-competent avian sarcoma leukosis virus (rCAS virus) and tumour virus A (TvA) receptor)88. Because of the increased spatial–temporal control over loss and gain of gene function that is afforded by these approaches, in some respects, the GEM created using these strategies may more accurately replicate the development of human breast cancer (BOX 2).

Do GEM recapitulate human breast cancer? In 1999, the US national Institutes of Health (nIH) Breast Cancer Think Tank and Annapolis pathology panel developed a consensus report on the comparative pathology of 39 breast cancer GEM and human breast cancers89. The main conclusion of this comprehensive analysis was that, overall, the histology of most tumours from GEM does not resemble the common types of breast cancer. However, many similarities between mouse and human tumours were identified: tumour formation resulted from multiple genetic mutations, tumours from GEM contained regions that resembled human breast cancer, and genes associated with human cancer induced cancer in mice. notable differences were identified, such as: most mouse tumours metastasize only to the lungs, contain less fibrosis and inflammation, and nearly all are hormone independent as opposed to approximately half of human breast cancers that are hormone dependent. In comparison to tumours from GEM, carcinogen-induced mammary tumours in rats are more frequently hormone dependent, and therefore provide a rodent model for investigating hormone action in breast cancer90 (BOX 3). Interestingly, several GEM such as the Myc, Erbb2 and

Ras mouse models demonstrated unique histologies when compared with other GEM. The panel concluded that these distinct phenotypes are significant and sug-gest that the initiating oncogene profoundly affects the tumour phenotype in mice and potentially in humans. In support of this, numerous studies have demonstrated that oncogene-specific signalling pathways promote tumour progression and disease recurrence91–94.

Although these results were encouraging, Cardiff, Green and colleagues warn that because of the diversity of human breast cancer and species differences, indi-vidual genetically engineered mouse models should not be expected to faithfully recapitulate all aspects of the human disease. Advances in genetic engineer-ing have improved our spatial–temporal control over gene expression allowing the development of geneti-cally engineered mouse models of breast cancer, which in some cases demonstrate features that more closely resemble the human disease95,96; however, most tumours from GEM still do not recapitulate the most common subtypes of breast cancer. Despite these limitations, it is important to acknowledge the impact that these experimental models have had on our understanding of the genetics and biology of breast cancer.

Over the last two decades much effort has been directed at determining the extent to which GEM mimic human breast cancer. not surprisingly, TP53, which is one of the most frequently mutated genes in breast cancer, and ERBB2, which is amplified in 25–30% of human breast cancers, have been studied most extensively97,98. For example, Aldaz and colleagues carried out serial analysis of gene expression (SAGE) of p53-null mouse tumours and human breast cancers and identified 72 genes that were commonly deregu-lated99. These results, combined with the pathological features of the p53-null tumours, including Er+ status in approximately 20% of the tumours, led these authors to conclude that the Trp53-null genetically engineered mouse model more accurately mimics human breast cancer than other GEM.

More recently, it has been shown that the somatic loss of Trp53 mediated by several Cre-recombinase strains results in variable tumour penetrance, latency and meta-static capacity that depends on the strain and parity of the Cre mice83. Interestingly, Trp53 deletion using Wap-Cre results in a high percentage of Er+/pr+ tumours, whereas tumours that arise in the MMTv-Cre mice were hormone-receptor negative. Tumours arising in these mice also showed amplification and overexpression of many genes that are involved in human breast cancer, including Myc and Erbb2. Conditional loss of both E-cadherin and Trp53 mediated by K14-Cre resulted in mammary tumours with striking resemblance to invasive lobular carcinomas, which is one of the most common types of breast cancer95. In addition, loss of E-cadherin significantly increased the metastatic rate of these tumours. The results of these studies indicate that the strategy used to drive transgene expression, which may affect the developmental timing and cell types in which the transgene is expressed, dramatically affects the tumour phenotype. Furthermore, these

Box 2 | Inducible and conditional genetically engineered mouse models

Advances in genetic engineering have allowed for more precise control over the loss and gain of gene function in genetically engineered mice (GEM). However, several of these approaches use the Wap (whey acidic protein) and MMTV (mouse mammary tumour virus) promoters and, therefore, are subject to the hormonal regulation and other features of these promoters. It is also important to consider that there are several strains of MMTV-Cre and Wap-Cre transgenic mice, and each differs with respect to the tissue specificity, developmental timing and cell types in which the Cre recombinase is expressed80,81. For example, when MMTV-Cre mice were bred to mice containing a conditional allele of p120 catenin, an essential gene, neonatal lethality resulted, indicating that conditional gene deletion strategies could result in unexpected phenotypes119. In contrast to germline deletions, Cre-mediated gene deletion results in gene loss in a fraction of cells and, in the case of partial loss of function, phenotypes may not be detected. Despite these potential limitations, tissue-selective Cre-mediated gene deletion or activation has provided invaluable tools for investigating genes that, when altered in the germ line, have detrimental affects on the health or survival of the animals, precluding their investigation in tumour formation and progression.

R E V I E W S

666 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

studies demonstrate that the Trp53 loss-of-function GEM develop tumours with many of the salient fea-tures of human breast cancer and, therefore, provide important tools to investigate the genetics and biology of this disease.

Seminal studies have also been carried out that com-pare Erbb2 genetically engineered mouse models and human breast cancer. Several strains of MMTv-Neu transgenic mice that contain either the wild-type or activated rat Erbb2 (also known as Neu) were generated in the late 1980s (REFS 77,100; for a review see REF 101). Mice bearing the wild-type Erbb2 allele under the control of the MMTv promoter exhibit spontaneous deletions in the transgene, leading to constitutive activation102. Knock-in mice that express the activated Erbb2 under the control of the endogenous promoter showed ampli-fication of this genomic region, much like that observed in human breast cancer96. Other genomic changes were observed, including amplifications and deletions that occur in other Erbb2 transgenic lines as well as human ErBB2+ breast cancers103,104. Microarray profiling studies that compare the different Erbb2 models demonstrate that, similar to ErBB2+ human breast cancers, tumours that arise in the knock-in mice show increased expression of growth factor receptor bound protein 7 (GrB7) and co-amplified with Erbb2 (CAB1), which is not detected in the other Erbb2 GEM104,105. Interestingly, in comparison to the MMTv-Neu mice, the knock-in mice show significantly increased tumour latency and an extremely low metastasis rate96. Therefore, these studies demonstrate that the promoter used to drive oncogene expression, which potentially affects expres-sion levels, developmental timing and the cell types in

which the oncogene is expressed, markedly affects the tumour phenotype.

When evaluating these models it is important to consider that ErBB2+ human breast cancers are aggressive cancers that display significantly shortened disease-free and overall survival97,106. Thus, the knock-in model, in which metastasis was rarely detected, does not seem to recapitulate ErBB2+ human breast cancer pathogenesis. For this reason, it is likely that the MMTv-driven Erbb2 models will continue to be used to examine how tumour suppressors and onco-genes modulate Erbb2-induced tumour promotion and progression. Despite these limitations, the knock-in studies demonstrate that for genes that are amplified in human breast cancer, using endogenous promoters to drive oncogene expression in GEM may provide models for investigating the mechanisms that regulate oncogene expression and induction of cooperating signalling pathways.

To determine the extent to which GEM reproduce the molecular features of the human disease, perou and colleagues107 recently performed a comprehensive interspecies analysis in which the molecular profiles of 13 GEM of breast cancer and a large panel of human breast cancers were compared. Strikingly, these studies corroborated the findings of the Annapolis pathology panel. For example, consistent with the conclusion that genotype correlates with phenotype, individual tumours from each model generally clustered together on a dendogram, indicating that they are molecularly most similar to tumours that arise from the same genetically engineered mouse model (FIG. 4). Several of the models also shared features with human breast cancer, including representations of luminal (MMTv-Neu, MMTv-pyMT, Wap-Myc and Wap-Int3) and basal (C3(1)-Tag, Wap-Tag and Brca1-deficient models) sub-types, as well as altered expression of genes associated with human breast cancer. However, no genetically engineered mouse model was representative of the Er+ luminal A subtype. The histological classification scheme that was developed by the Annapolis panel, coupled with the accumulating molecular profiling data, provide a foundation for comparing GEM and human breast cancer.

A notable conclusion from all of these studies is that the tumour phenotype, as defined by latency, histo-pathology and metastatic capability in GEM, is an amalgamation of the initiating oncogene, cell of origin and developmental timing of oncogenesis. The different genetically engineered mouse models of breast cancer, therefore, provide individual models that are useful for studying distinct signalling interactions that contribute to breast cancer progression and potentially for testing therapies that target these pathways. In this respect, recent studies have shown that the transplantation of tumours from GEM is a highly effective way to generate large cohorts of mammary tumour-bearing mice in a well-defined molecular and genetic background with a determined rate of tumour development and fre-quency of metastasis, and thus may provide a tractable method for using GEM as preclinical models74.

Box 3 | Modelling breast cancer in rats

Chemical carcinogenesis of the rat mammary gland has been used to investigate breast cancer for over 50 years120. To induce mammary tumours, rats are treated most commonly with 7,12-dimethylbenz(a)anthracene (DMBA) or N-nitroso-N-methylurea (NMU), and protocols have been developed to optimize the dose and developmental timing of carcinogenesis121–123. In contrast to most mammary tumours that arise in genetically engineered mice (GEM), which are hormone independent, chemically induced rat mammary tumours are generally hormone-dependent adenocarcinomas90. For this reason, the rat mammary carcinogenesis model has been utilized extensively to investigate hormone-dependent breast cancer and the protective role of pregnancy in breast cancer124–126. The tumour phenotype in the rat carcinogenesis models as defined by incidence, latency, multiplicity and histology is markedly influenced by the dose, developmental timing of carcinogenesis and parity of the host at the time of exposure, which probably affect the cell of origin and initiating oncogenic pathways. A histological classification scheme has been developed for these tumours, and comparative studies have demonstrated histological similarities between rat mammary tumours and human breast cancers90,127.

Although the rat mammary carcinogenesis model has been particularly useful for investigating the role of steroid hormones in breast cancer, there are several drawbacks of using rats as models for breast cancer. For example, rat mammary tumours rarely metastasize90, which is clearly a critical limitation. Compared with mice, the availability of genetic engineering strategies for rats, particularly nuclear transfer to create gene knockouts, have precluded the widespread use of rats as genetic models for cancer and other diseases. A mutagenesis strategy has been developed, which has been shown to be effective in generating Brca1 and Brca2 gene mutants128. However, efficient technologies to create complete gene knockouts in rats will be required to improve their utility for investigating breast cancer.

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 667

© 2007 Nature Publishing Group

Nature Reviews | Cancer

a

b

I II III IV V VI VII VIII IX X

FVB/

N W

ap-M

yc C

A02

-540

Brep

spi

ndlo

idFV

B/N

Wap

-Myc

CA

02-5

40B

spin

dloi

d FV

B/N

Wap

-Myc

CA

02-5

50A

spi

ndlo

idBA

LB/c

NO

RMA

L 10

0992

BALB

/c N

ORM

AL

1009

89FV

B/N

NO

RMA

L C

A02

-450

AFV

B/N

NO

RMA

L C

A04

-679

AFV

B/N

NO

RMA

L C

A02

-489

AFV

B/N

NO

RMA

L C

A04

-678

AFV

B/N

NO

RMA

L C

A04

-677

ABA

LB/c

NO

RMA

L 10

0993

BA

LB/c

NO

RMA

L 10

0991

BALB

/c N

ORM

AL

1009

90C

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/– 8

8a2

FVB/

N D

MBA

13 S

pind

le

FVB/

N D

MBA

11 S

pind

le

C57

BL6

MM

TV-C

re B

rca1

Co/

Co

Trp5

3+/–

108b

BALB

/c T

rp53

–/–

TRA

NSP

LAN

T 26

57R

FVB/

N D

MBA

12 S

pind

leBA

LB/c

Trp

53+/

– IR

C13

01.4

FVB/

N M

MTV

-Neu

#40

4B6

D2F

1 Wap

-T12

1 KS5

80FV

B/N

DM

BA 8

Squ

aFV

B/N

DM

BA 6

Squ

aFV

B/N

DM

BA 5

Squ

aC

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/– 8

8c1

BALB

/c W

ap-T

121 K

S556

BALB

/c W

ap-T

121 K

S555

FVB/

N W

ap-In

t3 C

A02

-575

AFV

B/N

MM

TV-W

nt1 C

A02

-506

AFV

B/N

DM

BA 2

Ade

noFV

B/N

MM

TV-P

yMT

'91

FVB/

N D

MBA

9re

p A

deno

squa

FVB/

N D

MBA

9 A

deno

squa

FVB/

N M

MTV

-Wnt

1 CA

02-4

93A

FVB/

N M

MTV

-Wnt

1 CA

02-4

86A

FV

B/N

MM

TV-W

nt1 C

A02

-478

AFV

B/N

MM

TV-W

nt1 C

A03

-634

AFV

B/N

MM

TV-W

nt1 C

A03

-587

AFV

B/N

DM

BA 1

Ade

noFV

B/N

DM

BA 4

Ade

noFV

B/N

DM

BA 3

Ade

noBA

LB/c

Brc

a1+/

– Tr

p53+

/– IR

B99

65.1

C57

BL6

MM

TV-C

re B

rca1

Co/

Co

Trp5

3+/–

172d

BALB

/c T

rp53

+/–

IR A

2989

.7C

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/– 10

6c1

BALB

/c T

rp53

+/–

IR 10

915.

7BA

LB/c

Brc

a1+/

– Tr

p53+

/– IR

B99

64.6

BALB

/c B

rca1

+/–

Trp5

3+/–

IR C

0912

.12BA

LB/c

Trp

53+/

– IR

C03

23.4

BALB

/c B

rca1

+/–

Trp5

3+/–

IR C

0912

.13BA

LB/c

Brc

a1+/

– Tr

p53+

/– IR

C03

79.5

BALB

/cTr

p53+

/– IR

C13

01.1

C57

BL6

MM

TV-C

re B

rca1

Co/

Co

Trp5

3+/–

145a

2C

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/–t

100a

BALB

/c B

rca1

+/–

Trp5

3+/–

C09

17.4

BALB

/c B

rca1

+/–

Trp5

3+/–

B112

9.4

FVB/

N M

MTV

-Wnt

1 CA

02-4

67A

FVB/

N M

MTV

-Wnt

1 CA

04-6

83A

FVB/

N M

MTV

-Wnt

1 CA

04-6

76A

FVB/

N M

MTV

-Wnt

1 CA

02-5

70B

BALB

/c T

rp53

–/–

TRA

NSP

LAN

T 43

04R

BALB

/c T

rp53

–/–

TRA

NSP

LAN

T 39

41R

BALB

/c T

rp53

–/–

TRA

NSP

LAN

T 39

39R

BALB

/c T

rp53

+/–

IR a

5824

.7BA

LB/c

Trp

53 –

/– T

RAN

SPLA

NT

1634

R C

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/– 11

3aC

57BL

6 M

MTV

-Cre

Brc

a1C

o/C

o Tr

p53+

/– 12

9BA

LB/c

Trp

53+/

– IR

A14

46.1

FVB/

N M

MTV

-Wnt

1 CA

02-5

70A

FVB/

N M

MTV

-PyM

T 43

0FV

B/N

MM

TV-N

eu C

A01

-431

AFV

B/N

MM

TV-N

eu 6

9331

FVB/

N M

MTV

-Neu

CA

01-4

16C

FVB/

N M

MTV

-Neu

CA

01-4

32A

FVB/

N M

MTV

-Neu

CA

01-4

16A

FVB/

N M

MTV

-Neu

8-2

-99

FVB/

N M

MTV

-Neu

CA

05-8

75A

FVB/

N M

MTV

-Neu

CA

05-8

61A

FVB/

N M

MTV

-Neu

7-6

-99

FVB/

N M

MTV

-PyM

T '8

9FV

B/N

MM

TV-P

yMT

'91#

3FV

B/N

MM

TV-P

yMT

'91#

2FV

B/N

MM

TV-P

yMT

'31FV

B/N

MM

TV-P

yMT

575

FVB/

N W

ap-M

yc C

A02

-569

AFV

B/N

Wap

-Myc

CA

02-5

45A

FVB/

N W

ap-M

yc C

A02

-567

CFV

B/N

Wap

-Myc

CA

05-8

67A

FVB/

N W

ap-M

yc C

A02

-548

AFV

B/N

Wap

-Myc

CA

02-5

79C

FVB/

N W

ap-M

yc C

A02

-549

AFV

B/N

Wap

-Myc

CA

02-5

79F

FVB/

N W

ap-M

yc C

A02

-540

AFV

B/N

Wap

-Myc

CA

02-5

44A

FV

B/N

Wap

-Myc

CA

05-8

69A

FVB/

N W

ap-In

t3 C

A02

-566

AFV

B/N

Wap

-Int3

CA

01-4

34B

FVB/

N W

ap-In

t3 C

A01

-434

AFV

B/N

Wap

-Int3

CA

02-4

37A

FVB/

N W

ap-In

t3 C

A01

-426

AFV

B/N

Wap

-Int3

CA

01-4

33A

rep

FVB/

N W

ap-In

t3 C

A01

-433

Are

pFV

B/N

Wap

-Int3

CA

01-4

33A

C57

BL6

MM

TV-C

re B

rca1

Co/

Co

Trp5

3+/–

96b

B6

D2F

1 Wap

-T12

1 KS1

50B6

D2F

1 Wap

-T12

1 KS6

44B6

D2F

1 Wap

-T12

1 KS6

43B6

D2F

1 Wap

-T12

1 Trp

53+/

– KS

581

C57

BL6

Wap

-Tag

CA

-215

AC

57BL

6 W

ap-T

ag C

A-2

13A

C57

BL6

Wap

-Tag

CA

-226

AC

57BL

6 W

ap-T

ag C

A-2

26B

C57

BL6

Wap

-Tag

CA

-224

AFV

B/N

C3(

1)-Ta

g #8

4FV

B/N

C3(

1)-Ta

g E2

9-5A

-645

FVB/

N C

3(1)-

Tag

#86

FVB/

N C

3(1)-

Tag

E29-

2A-6

32FV

B/N

C3(

1)-Ta

g E2

9-1A

-614

FVB/

N C

3(1)-

Tag

#76

FVB/

N C

3(1)-

Tag

#74

FVB/

N C

3(1)-

Tag

#72

Wap-Int3Human subtype

MMTV-PyMTMMTV-NeuWap-MycTrp53–/– transplantDMBAMMTV-Wnt1Trp53+/– IRBrca1+/– Trp53+/– IRMMTV-Cre Brca1 Trp53+/–

Wap-TagC3(1)-TagWap-T121Normal

HER2 statusER status

Do tumours from GEM contain tumour-initiating cells? To date there are no reported studies in which the cancer stem cell hypothesis has been investigated in breast cancer genetically engineered mouse models, although several are forthcoming (unpublished observations, J.M. rosen and M. Zhang). The isolation of specific subpopulations and limiting dilution serial transplan-tation experiments are required to determine whether

each genetically engineered mouse model contains a subpopulation of tumour-initiating cells and whether these populations express similar or distinct markers. Oncogene activation or tumour suppressor deletion in GEM is usually targeted to a high percentage of cells, which may not represent the quiescent stem cell popu-lation, but instead more differentiated progenitors or their progeny. One exception is the targeted expression

Figure 4 |MolecularprofilingofmammarytumoursfromGeMandcomparisonwithhumanbreastcancerprofiles.a | A dendogram representing the intrinsic gene set cluster analysis of the molecular profiles of mammary tumours from 13 breast cancer genetically engineered mouse models is shown. The tumours fall into 10 groups (which are indicated by roman numerals and colour), which suggests that in general the tumours from different genetically engineered mice (GEM) are genetically distinct. However, there is some overlap, as seen by the clustering of certain tumours on the dendogram. The colours correspond to the tumours from GEM listed below the dendogram that were primarily associated with that group. Tumours from six of the models (Wap-Myc, MMTV-Neu, Wap-Int3, Wap-Tag, C3(1)-Tag and MMTV-PyMT) exhibited unique gene-expression patterns that were homogeneous within each model. By contrast, four other models (Wap-T121, MMTV-Wnt1, Brca1Co/Co;MMTV-Cre;Trp53+/– and DMBA-induced) showed heterogeneity in their expression profiles, and thus fell into several groups. b | A dendogram representation of an unsupervised cluster analysis of the combined gene-expression profiles for 232 human breast cancers and 122 mouse mammary tumour samples obtained from 13 GEM. The colour-coded bars below the dendogram represent individual samples. The first two rows underneath the dendogram show the ER (oestrogen receptor)and ERBB2 (also known as HER2) status of the human tumours, where red is positive, green is negative and gray is not determined. The third row shows the subtype of the human breast cancer samples by colour, where red is basal, blue is luminal, pink is ERBB2+/ER–, yellow is claudin-low, and green is normal breast-like. The rest of the rows represent tumours from the GEM listed on the right. Several GEM show similarities to human breast cancer, including features of the luminal (MMTV-Neu, MMTV-PyMT, Wap-Myc and Wap-Int3) and basal (C3(1)-Tag, Wap-Tag and Brca1-deficient models) subtypes. None of these genetically engineered mouse models were representative of ER+ breast cancer. Furthermore, the tumours from MMTV-Neu GEM were more similar to human luminal tumours than to the human ERBB2+ tumours. DMBA, 7,12-dimethylbenz(a)anthracene. Image reproduced from REF. 107.

R E V I E W S

668 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

Dormant tumour-initiating cellsThe cells within a tumour that are not actively cycling and are capable of giving rise to a new tumour.

Neoadjuvant chemotherapyA drug treatment given to reduce the size of tumours before surgery.

of secreted factors such as WnT1 (wingless type MMTv integration family, member 1), which can potentially act on adjacent stem or progenitor cells to produce tumours that contain multiple cell lineages108. However, tumours that arise in GEM containing down-stream signalling components of the Wnt pathway demonstrate similar phenotypes, indicating that this pathway may preferentially target progenitor cells.

Accumulating evidence suggests that other GEM contain tumour-initiating cells, which may be respon-sible for recurrence. Chodosh and colleagues91,93,94 have demonstrated oncogene-independent tumour recurrence using inducible GEM, and it has been demonstrated recently that these tumours contain a subpopulation of dormant tumour-initiating cells109. Thus, breast cancer genetically engineered mouse models may provide distinct models in which to char-acterize and investigate the role of tumour-initiating cells in mammary tumour formation, progression and therapeutic resistance.

The future of breast cancer modelsFor the last three decades, breast cancer models have been at the forefront of cancer research. The pioneering work of leder, Muller and colleagues, who developed the first genetically engineered mouse models of cancer, set the stage for the application and development of the breast cancer GEM that are widely used today. Furthermore, the work of Bissell, Brugge and colleagues in establishing 3D culture methods for breast epithelial and cancer cells has provided invalu-able models to dissect the complex signalling inter-actions that are difficult to investigate in vivo. An emerging application of the GEM of breast cancer is the examination of primary mammary epithelial cells or tumour cells that are derived from these mice in 3D cultures or other in vitro assays, allowing the deline-ation of signalling mechanisms that are not easily investigated in vivo. What is learned in these culture studies can then be validated in vivo.

Established cell lines exhibit many features of breast cancer, but can we improve their utility? As proposed by Gray and colleagues13, subtype cell lines can be used as a system to investigate signalling pathways that regulate tumour initiation and progression and as preclinical models both in culture and as xenografts. This system can be used in heterotypic 3D cultures to investigate crucial tumour–stromal interactions. Furthermore, by combining molecular profiling to identify breast cell lineages and cancer subtypes with improved methods for immortalizing and culturing cells from clinical isolates6,16 it should be possible to generate new cell lines that may more accurately recapitulate these cell types. Advances in breast stem cell biology and the identification of more markers and better methods for the isolation, characterization and genetic manipulation of these cells are essential for the future investigation of breast cancer.

numerous studies have demonstrated the utility of xenografts and GEM and their relevance to understanding the genetics and biology of breast cancer, but how can we

optimize these models? Our current understanding of the role of the immune system in promoting tumour formation and progression is a particular limitation for improving these models. Despite recent advances in generating breast cancer xenografts70, this approach is hindered by low transplantation efficiencies, which is probably due to the need for immunocompromised mice. Advances in isolating and characterizing tumour-promoting immune cells and methods for their co-transplantation with tumour cells may improve engraftment efficiencies. Another challenge is the availability of models that faith-fully recapitulate metastatic disease, and accumulating evidence has demonstrated that the immune system plays an essential part in establishing the metastatic niche110. The development of models that metastasize not only to the lungs, but also to other common sites (for example, the lymph nodes, bone, liver and brain) is crucial, and progress has been made in generating these models111. Thus, a better understanding of the role of the immune system and microenvironment in breast cancer will help to improve both xenograft and metastasis models.

Cell lines and xenografts have been used exten-sively as preclinical models69, but how can we improve their utility? Can we effectively use GEM as preclinical models? Certain breast cancer cell lines may provide useful tools for high-throughput screening of small molecules and rnAi (rnA interference) libraries as a first line of investigation to identify the interacting pathways that are important for tumour-initiating cell self-renewal and survival112. Using the subtype cell line system13 in 3D cultures and as xenografts may strengthen the preclinical utility of these models. Subtype system xenografts may also provide useful models for evaluating the effects of conventional thera-peutics, including chemotherapy and radiation therapy in combination with novel targeted therapeutics. Furthermore, xenografts of matched pre- and post-neoadjuvant treated breast cancers may provide a pow-erful way to investigate therapeutic efficacy. However, the widespread use of this approach will require meth-ods that increase transplantation efficiency. Finally, recent advances in optimizing breast cancer geneti-cally engineered mouse models74 and in generating metastasis models110 may enhance the application of GEM for evaluating therapeutics.

ConclusionsWe have attempted to provide a representative over-view of the cell culture, xenograft and genetically engineered mouse models that are widely used for investigating breast cancer. The accumulating molec-ular profiling and genomic studies from cell lines, GEM and human breast cancers provide a frame-work in which to more precisely evaluate and select model systems to test specific hypotheses. Because of the complexity and heterogeneity of breast cancer no individual model recapitulates all aspects of this disease. Therefore, the future of modelling breast cancer will rely on an integrated and multi-systems approach, which we propose is the most powerful way to investigate breast cancer.

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 669

© 2007 Nature Publishing Group

1.   American Cancer Society. Cancer facts and figures 2007. (American Cancer Society, 2007).

2.   Ferlay, J. et al. Estimates of the cancer incidence and mortality in Europe in 2006. Ann. Oncol. 18, 581–592 (2007).

3.   Ravdin, P. M. et al. The decrease in breast-cancer incidence in 2003 in the United States. N. Engl. J. Med. 356, 1670–1674 (2007).

4.   Lacroix, M. & Leclercq, G. Relevance of breast cancer cell lines as models for breast tumours: an update. Breast Cancer Res. Treat. 83, 249–289 (2004).

5.   Hahn, W. C. & Weinberg, R. A. Rules for making human tumor cells. N. Engl. J. Med. 347, 1593–1603 (2002).

6.   Rangarajan, A., Hong, S. J., Gifford, A. & Weinberg, R. A. Species- and cell type-specific requirements for cellular transformation. Cancer Cell 6, 171–183 (2004).

7.   Rangarajan, A. & Weinberg, R. A. Comparative biology of mouse versus human cells: modelling human cancer in mice. Nature Rev. Cancer 3, 952–959 (2003).

8.   Nandi, S., Guzman, R. C. & Yang, J. Hormones and mammary carcinogenesis in mice, rats, and humans: a unifying hypothesis. Proc. Natl Acad. Sci. USA 92, 3650–3657 (1995).

9.   Burdall, S. E., Hanby, A. M., Lansdown, M. R. & Speirs, V. Breast cancer cell lines: friend or foe? Breast Cancer Res. 5, 89–95 (2003).

10.   Perou, C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).This seminal molecular profiling study of human breast cancers identified five distinct subtypes of ductal carcinoma.

11.   Ross, D. T. et al. Systematic variation in gene expression patterns in human cancer cell lines. Nature Genet. 24, 227–235 (2000).

12.   Charafe-Jauffret, E. et al. Gene expression profiling of breast cell lines identifies potential new basal markers. Oncogene 25, 2273–2284 (2006).

13.   Neve, R. M. et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10, 515–527 (2006).This comprehensive study, which compares the molecular profiles and genomic alterations of 51 breast cancer cell lines and human breast tumours, highlights the similarities and differences between cell lines and primary tumours and suggests that when subtype cell lines are used as a system they provide powerful models for investigating breast cancer.

14.   Van’t Veer, L. J. & Weigelt, B. Road map to metastasis. Nature Med. 9, 999–1000 (2003).

15.   Weigelt, B., Bosma, A. J., Hart, A. A., Rodenhuis, S. & van ‘t Veer, L. J. Marker genes for circulating tumour cells predict survival in metastasized breast cancer patients. Br. J. Cancer 88, 1091–1094 (2003).

16.   Dontu, G. et al. In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells. Genes Dev. 17, 1253–1270 (2003).

17.   Villadsen, R. et al. Evidence for a stem cell hierarchy in the adult human breast. J. Cell Biol. 177, 87–101 (2007).

18.   Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J. & Clarke, M. F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA 100, 3983–3988 (2003).

19.   Ponti, D. et al. Isolation and in vitro propagation of tumorigenic breast cancer cells with stem/progenitor cell properties. Cancer Res. 65, 5506–5511 (2005).

20.   Polyak, K. Molecular alterations in ductal carcinoma in situ of the breast. Curr. Opin. Oncol. 14, 92–96 (2002).

21.   Reya, T., Morrison, S. J., Clarke, M. F. & Weissman, I. L. Stem cells, cancer, and cancer stem cells. Nature 414, 105–111 (2001).

22.   Wicha, M. S., Liu, S. & Dontu, G. Cancer stem cells: an old idea — a paradigm shift. Cancer Res. 66, 1883–1890; discussion 1895–1886 (2006).

23.   Dalerba, P., Cho, R. W. & Clarke, M. F. Cancer stem cells: models and concepts. Annu. Rev. Med. 58, 267–284 (2007).

24.   Kuperwasser, C. et al. Reconstruction of functionally normal and malignant human breast tissues in mice. Proc. Natl Acad. Sci. USA 101, 4966–4971 (2004).

25.   Dontu, G. & Wicha, M. S. Survival of mammary stem cells in suspension culture: implications for stem cell biology and neoplasia. J. Mammary Gland Biol. Neoplasia 10, 75–86 (2005).

26.   Phillips, T. M., McBride, W. H. & Pajonk, F. The response of CD24–/low/CD44+ breast cancer-initiating cells to radiation. J. Natl Cancer Inst. 98, 1777–1785 (2006).

27.   Chen, M. S. et al. Wnt/β-catenin mediates radiation resistance of Sca1+ progenitors in an immortalized mammary gland cell line. J. Cell Sci. 120, 468–477 (2007).

28.   Woodward, W. A. et al. WNT/β-catenin mediates radiation resistance of mouse mammary progenitor cells. Proc. Natl Acad. Sci. USA 104, 618–623 (2007).

29.   Sheridan, C. et al. CD44+/CD24– breast cancer cells exhibit enhanced invasive properties: an early step necessary for metastasis. Breast Cancer Res. 8, R59 (2006).

30.   Shipitsin, M. et al. Molecular definition of breast tumor heterogeneity. Cancer Cell 11, 259–273 (2007).

31.   Abraham, B. K. et al. Prevalence of CD44+/CD24–/low cells in breast cancer may not be associated with clinical outcome but may favor distant metastasis. Clin. Cancer Res. 11, 1154–1159 (2005).

32.   Liu, R. et al. The prognostic role of a gene signature from tumorigenic breast-cancer cells. N. Engl. J. Med. 356, 217–226 (2007).

33.   Armstrong, L. et al. Phenotypic characterization of murine primitive hematopoietic progenitor cells isolated on basis of aldehyde dehydrogenase activity. Stem Cells 22, 1142–1151 (2004).

34.   Fillmore, C. & Kuperwasser, C. Human breast cancer stem cell markers CD44 and CD24: enriching for cells with functional properties in mice or in man? Breast Cancer Res. 9, 303 (2007).

35.   Ross, D. T. & Perou, C. M. A comparison of gene expression signatures from breast tumors and breast tissue derived cell lines. Dis. Markers 17, 99–109 (2001).

36.   Kenny, P. A. et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol. Oncol. 1, 84–96 (2007).This study compares gene expression, genomic alterations and morphologies of 27 breast cancer cell lines cultured in 2D versus 3D conditions, which indicates that 3D cultures more precisely mimic the in vivo environment.

37.   Li, C. et al. Cell type and culture condition-dependent alternative splicing in human breast cancer cells revealed by splicing-sensitive microarrays. Cancer Res. 66, 1990–1999 (2006).

38.   Shaw, K. R., Wrobel, C. N. & Brugge, J. S. Use of three-dimensional basement membrane cultures to model oncogene-induced changes in mammary epithelial morphogenesis. J. Mammary Gland Biol. Neoplasia 9, 297–310 (2004).

39.   Debnath, J. & Brugge, J. S. Modelling glandular epithelial cancers in three-dimensional cultures. Nature Rev. Cancer 5, 675–688 (2005).

40.   Paszek, M. J. & Weaver, V. M. The tension mounts: mechanics meets morphogenesis and malignancy. J. Mammary Gland Biol. Neoplasia 9, 325–342 (2004).

41.   Lee, G. Y., Kenny, P. A., Lee, E. H. & Bissell, M. J. Three-dimensional culture models of normal and malignant breast epithelial cells. Nature Methods 4, 359–365 (2007).

42.   Paszek, M. J. et al. Tensional homeostasis and the malignant phenotype. Cancer Cell 8, 241–254 (2005).

43.   Chan, S. K., Hill, M. E. & Gullick, W. J. The role of the epidermal growth factor receptor in breast cancer. J. Mammary Gland Biol. Neoplasia 11, 3–11 (2006).

44.   van Golen, K. L. Inflammatory breast cancer: relationship between growth factor signaling and motility in aggressive cancers. Breast Cancer Res. 5, 174–179 (2003).

45.   Dillon, R. L., White, D. E. & Muller, W. J. The phosphatidyl inositol 3-kinase signaling network: implications for human breast cancer. Oncogene 26, 1338–1345 (2007).

46.   Kenny, P. A. & Bissell, M. J. Targeting TACE-dependent EGFR ligand shedding in breast cancer. J. Clin. Invest. 117, 337–345 (2007).

47.   Joyce, J. A. Therapeutic targeting of the tumor microenvironment. Cancer Cell 7, 513–520 (2005).

48.   Albini, A. & Sporn, M. B. The tumour microenvironment as a target for chemoprevention. Nature Rev. Cancer 7, 139–147 (2007).

49.   Fukino, K., Shen, L., Patocs, A., Mutter, G. L. & Eng, C. Genomic instability within tumor stroma and clinicopathological characteristics of sporadic primary invasive breast carcinoma. JAMA 297, 2103–2111 (2007).

50.   Pukrop, T. et al. Wnt 5a signaling is critical for macrophage-induced invasion of breast cancer cell lines. Proc. Natl Acad. Sci. USA 103, 5454–5459 (2006).

51.   Hagemann, T. et al. Enhanced invasiveness of breast cancer cell lines upon co-cultivation with macrophages is due to TNF-α dependent up-regulation of matrix metalloproteases. Carcinogenesis 25, 1543–1549 (2004).

52.   Goswami, S. et al. Macrophages promote the invasion of breast carcinoma cells via a colony-stimulating factor-1/epidermal growth factor paracrine loop. Cancer Res. 65, 5278–5283 (2005).

53.   Tsutsui, S. et al. Macrophage infiltration and its prognostic implications in breast cancer: the relationship with VEGF expression and microvessel density. Oncol. Rep. 14, 425–431 (2005).

54.   Leek, R. D., Landers, R. J., Harris, A. L. & Lewis, C. E. Necrosis correlates with high vascular density and focal macrophage infiltration in invasive carcinoma of the breast. Br. J. Cancer 79, 991–995 (1999).

55.   Lin, E. Y. et al. Macrophages regulate the angiogenic switch in a mouse model of breast cancer. Cancer Res. 66, 11238–11246 (2006).

56.   Heppner, G. H., Miller, F. R. & Shekhar, P. M. Nontransgenic models of breast cancer. Breast Cancer Res. 2, 331–334 (2000).

57.   Balkwill, F., Charles, K. A. & Mantovani, A. Smoldering and polarized inflammation in the initiation and promotion of malignant disease. Cancer Cell 7, 211–217 (2005).

58.   Schwertfeger, K. L., Rosen, J. M. & Cohen, D. A. Mammary gland macrophages: pleiotropic functions in mammary development. J. Mammary Gland Biol. Neoplasia 11, 229–238 (2006).

59.   Hovey, R. C., McFadden, T. B. & Akers, R. M. Regulation of mammary gland growth and morphogenesis by the mammary fat pad: a species comparison. J. Mammary Gland Biol. Neoplasia 4, 53–68 (1999).

60.   Weigelt, B., Peterse, J. L. & van ‘t Veer, L. J. Breast cancer metastasis: markers and models. Nature Rev. Cancer 5, 591–602 (2005).

61.   Minn, A. J. et al. Genes that mediate breast cancer metastasis to lung. Nature 436, 518–524 (2005).A breast cancer cell line xenograft metastasis model was used to identify a metastasis gene signature that could identify patients who would develop metastatic disease.

62.   Kluger, H. M. et al. Using a xenograft model of human breast cancer metastasis to find genes associated with clinically aggressive disease. Cancer Res. 65, 5578–5587 (2005).

63.   Montel, V., Huang, T. Y., Mose, E., Pestonjamasp, K. & Tarin, D. Expression profiling of primary tumors and matched lymphatic and lung metastases in a xenogeneic breast cancer model. Am. J. Pathol. 166, 1565–1579 (2005).

64.   Liu, S. et al. Hedgehog signaling and Bmi-1 regulate self-renewal of normal and malignant human mammary stem cells. Cancer Res. 66, 6063–6071 (2006).

65.   Prendergast, G. C. & Jaffee, E. M. Cancer immunologists and cancer biologists: why we didn’t talk then but need to now. Cancer Res. 67, 3500–3504 (2007).

66.   Voskoglou-Nomikos, T., Pater, J. L. & Seymour, L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin. Cancer Res. 9, 4227–4239 (2003).

67.   Shoemaker, R. H. The NCI60 human tumour cell line anticancer drug screen. Nature Rev. Cancer 6, 813–823 (2006).

68.   Johnson, J. I. et al. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br. J. Cancer 84, 1424–1431 (2001).

69.   Sharpless, N. E. & Depinho, R. A. The mighty mouse: genetically engineered mouse models in cancer drug development. Nature Rev. Drug Discov. 5, 741–754 (2006).

70.   Proia, D. A. & Kuperwasser, C. Reconstruction of human mammary tissues in a mouse model. Nature Protoc. 1, 206–214 (2006).

71.   Orimo, A. et al. Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell 121, 335–348 (2005).

72.   MacDonald, I. C. & Chambers, A. F. Breast cancer metastasis progression as revealed by intravital videomicroscopy. Expert Rev. Anticancer Ther. 6, 1271–1279 (2006).

73.   Wyckoff, J. B. et al. Direct visualization of macrophage-assisted tumor cell intravasation in mammary tumors. Cancer Res. 67, 2649–2656 (2007).

R E V I E W S

670 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group

74.   Varticovski, L. et al. Accelerated preclinical testing using transplanted tumors from genetically engineered mouse breast cancer models. Clin. Cancer Res. 13, 2168–2177 (2007).

75.   Guy, C. T., Cardiff, R. D. & Muller, W. J. Induction of mammary tumors by expression of polyomavirus middle T oncogene: a transgenic mouse model for metastatic disease. Mol. Cell. Biol. 12, 954–961 (1992).

76.   Guy, C. T. et al. Expression of the Neu protooncogene in the mammary epithelium of transgenic mice induces metastatic disease. Proc. Natl Acad. Sci. USA 89, 10578–10582 (1992).

77.   Muller, W. J., Sinn, E., Pattengale, P. K., Wallace, R. & Leder, P. Single-step induction of mammary adenocarcinoma in transgenic mice bearing the activated c-Neu oncogene. Cell 54, 105–115 (1988).

78.   Sinn, E. et al. Coexpression of MMTV/v-Ha-ras and MMTV/c-myc genes in transgenic mice: synergistic action of oncogenes in vivo. Cell 49, 465–475 (1987).

79.   Gunther, E. J. et al. A novel doxycycline-inducible system for the transgenic analysis of mammary gland biology. FASEB J. 16, 283–292 (2002).

80.   Wagner, K. U. et al. Spatial and temporal expression of the Cre gene under the control of the MMTV-LTR in different lines of transgenic mice. Transgenic Res. 10, 545–553 (2001).

81.   Wagner, K. U. et al. Cre-mediated gene deletion in the mammary gland. Nucleic Acids Res. 25, 4323–4330 (1997).

82.   Jonkers, J. et al. Synergistic tumor suppressor activity of BRCA2 and p53 in a conditional mouse model for breast cancer. Nature Genet. 29, 418–425 (2001).

83.   Lin, S. C. et al. Somatic mutation of p53 leads to estrogen receptor α-positive and -negative mouse mammary tumors with high frequency of metastasis. Cancer Res. 64, 3525–3532 (2004).

84.   Utomo, A. R., Nikitin, A. Y. & Lee, W. H. Temporal, spatial, and cell type-specific control of Cre-mediated DNA recombination in transgenic mice. Nature Biotech. 17, 1091–1096 (1999).

85.   Loonstra, A. et al. Growth inhibition and DNA damage induced by Cre recombinase in mammalian cells. Proc. Natl Acad. Sci. USA 98, 9209–9214 (2001).

86.   Soyal, S. M. et al. Cre-mediated recombination in cell lineages that express the progesterone receptor. Genesis 41, 58–66 (2005).

87.   Mukherjee, A. et al. Targeting iCre expression to murine progesterone receptor cell-lineages using bacterial artificial chromosome transgenesis. Genesis 44, 601–610 (2006).

88.   Du, Z. et al. Introduction of oncogenes into mammary glands in vivo with an avian retroviral vector initiates and promotes carcinogenesis in mouse models. Proc. Natl Acad. Sci. USA 103, 17396–17401 (2006).

89.   Cardiff, R. D. et al. The mammary pathology of genetically engineered mice: the consensus report and recommendations from the Annapolis meeting. Oncogene 19, 968–988 (2000).This is a seminal report on the comparative pathology and biology of mammary tumours from GEM and human breast cancers.

90.   Russo, J. & Russo, I. H. Atlas and histologic classification of tumors of the rat mammary gland. J. Mammary Gland Biol. Neoplasia 5, 187–200 (2000).

91.   Gunther, E. J. et al. Impact of p53 loss on reversal and recurrence of conditional Wnt-induced tumorigenesis. Genes Dev. 17, 488–501 (2003).

92.   Desai, K. V. et al. Initiating oncogenic event determines gene-expression patterns of human breast cancer models. Proc. Natl Acad. Sci. USA 99, 6967–6972 (2002).This molecular profiling study compares six widely used genetically engineered mouse models of breast cancer with each other and with normal mammary glands to identify oncogene-specific and nonspecific pathways that contribute to tumour development and progression.

93.   Moody, S. E. et al. Conditional activation of Neu in the mammary epithelium of transgenic mice results in reversible pulmonary metastasis. Cancer Cell 2, 451–461 (2002).

94.   Boxer, R. B., Jang, J. W., Sintasath, L. & Chodosh, L. A. Lack of sustained regression of c-MYC-induced mammary adenocarcinomas following brief or prolonged MYC inactivation. Cancer Cell 6, 577–586 (2004).

95.   Derksen, P. W. et al. Somatic inactivation of E-cadherin and p53 in mice leads to metastatic lobular

mammary carcinoma through induction of anoikis resistance and angiogenesis. Cancer Cell 10, 437–449 (2006).

96.   Andrechek, E. R. et al. Amplification of the Neu/ErbB‑2 oncogene in a mouse model of mammary tumorigenesis. Proc. Natl Acad. Sci. USA 97, 3444–3449 (2000).

97.   Slamon, D. J. et al. Human breast cancer: correlation of relapse and survival with amplification of the HER‑2/Neu oncogene. Science 235, 177–182 (1987).

98.   Elledge, R. M. & Allred, D. C. Prognostic and predictive value of p53 and p21 in breast cancer. Breast Cancer Res. Treat. 52, 79–98 (1998).

99.   Hu, Y. et al. From mice to humans: identification of commonly deregulated genes in mammary cancer via comparative SAGE studies. Cancer Res. 64, 7748–7755 (2004).

100.  Bouchard, L., Lamarre, L., Tremblay, P. J. & Jolicoeur, P. Stochastic appearance of mammary tumors in transgenic mice carrying the MMTV/c-Neu oncogene. Cell 57, 931–936 (1989).

101.  Ursini-Siegel, J., Schade, B., Cardiff, R. D. & Muller, W. J. Insights from transgenic mouse models of ERBB2-induced breast cancer. Nature Rev. Cancer 7, 389–397 (2007).

102.  Siegel, P. M., Dankort, D. L., Hardy, W. R. & Muller, W. J. Novel activating mutations in the Neu proto-oncogene involved in induction of mammary tumors. Mol. Cell. Biol. 14, 7068–7077 (1994).

103.  Montagna, C., Andrechek, E. R., Padilla-Nash, H., Muller, W. J. & Ried, T. Centrosome abnormalities, recurring deletions of chromosome 4, and genomic amplification of HER2/Neu define mouse mammary gland adenocarcinomas induced by mutant HER2/Neu. Oncogene 21, 890–898 (2002).

104.  Hodgson, J. G. et al. Copy number aberrations in mouse breast tumors reveal loci and genes important in tumorigenic receptor tyrosine kinase signaling. Cancer Res. 65, 9695–9704 (2005).

105.  Andrechek, E. R. et al. Gene expression profiling of Neu-induced mammary tumors from transgenic mice reveals genetic and morphological similarities to ErbB2-expressing human breast cancers. Cancer Res. 63, 4920–4926 (2003).

106.  Slamon, D. J. et al. Studies of the HER‑2/Neu proto-oncogene in human breast and ovarian cancer. Science 244, 707–712 (1989).

107.  Herschkowitz, J. I. et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol. 8, R76 (2007).This molecular profiling study compares 13 widely used genetically engineered mouse models of breast cancer with human breast cancers to provide a framework for comparing GEM and human breast cancer.

108.  Li, Y. et al. Evidence that transgenes encoding components of the Wnt signaling pathway preferentially induce mammary cancers from progenitor cells. Proc. Natl Acad. Sci. USA 100, 15853–15858 (2003).

109.  Gestl, S. A., Leonard, T. L., Biddle, J. L., Debies, M. T. & Gunther, E. J. Dormant Wnt-initiated mammary cancer can participate in reconstituting functional mammary glands. Mol. Cell. Biol. 27, 195–207 (2007).

110.  Welm, A. L. et al. The macrophage-stimulating protein pathway promotes metastasis in a mouse model for breast cancer and predicts poor prognosis in humans. Proc. Natl Acad. Sci. USA 104, 7570–7575 (2007).

111.  Kuperwasser, C. et al. A mouse model of human breast cancer metastasis to human bone. Cancer Res. 65, 6130–6138 (2005).

112.  Westbrook, T. F. et al. A genetic screen for candidate tumor suppressors identifies REST. Cell 121, 837–848 (2005).

113.  Dobie, K. W. et al. Variegated transgene expression in mouse mammary gland is determined by the transgene integration locus. Proc. Natl Acad. Sci. USA 93, 6659–6664 (1996).

114.  Choi, Y. W., Henrard, D., Lee, I. & Ross, S. R. The mouse mammary tumor virus long terminal repeat directs expression in epithelial and lymphoid cells of different tissues in transgenic mice. J. Virol. 61, 3013–3019 (1987).

115.  Henrard, D. & Ross, S. R. Endogenous mouse mammary tumor virus is expressed in several organs in addition to the lactating mammary gland. J. Virol. 62, 3046–3049 (1988).

116.  Wen, J., Kawamata, Y., Tojo, H., Tanaka, S. & Tachi, C. Expression of whey acidic protein (WAP) genes in

tissues other than the mammary gland in normal and transgenic mice expressing mWAP/hGH fusion gene. Mol. Reprod. Dev. 41, 399–406 (1995).

117.  Cardiff, R. D. Validity of mouse mammary tumour models for human breast cancer: comparative pathology. Microsc. Res. Tech. 52, 224–230 (2001).

118.  Wagner, K. U. Models of breast cancer: quo vadis, animal modeling? Breast Cancer Res. 6, 31–38 (2004).

119.  Davis, M. A. & Reynolds, A. B. Blocked acinar development, E-cadherin reduction, and intraepithelial neoplasia upon ablation of p120-catenin in the mouse salivary gland. Dev. Cell 10, 21–31 (2006).

120.  Huggins, C., Grand, L. C. & Brillantes, F. P. Mammary cancer induced by a single feeding of polymucular hydrocarbons, and its suppression. Nature 189, 204–207 (1961).

121.  Russo, I. H. & Russo, J. Developmental stage of the rat mammary gland as determinant of its susceptibility to 7,12-dimethylbenz[a]anthracene. J. Natl Cancer Inst. 61, 1439–1449 (1978).

122.  Thompson, H. J., Adlakha, H. & Singh, M. Effect of carcinogen dose and age at administration on induction of mammary carcinogenesis by 1-methyl-1-nitrosourea. Carcinogenesis 13, 1535–1539 (1992).

123.  Thompson, H. J. & Meeker, L. D. Induction of mammary gland carcinomas by the subcutaneous injection of 1-methyl-1-nitrosourea. Cancer Res. 43, 1628–1629 (1983).

124.  Russo, J. et al. Molecular basis of pregnancy-induced breast cancer protection. Eur. J. Cancer Prev. 15, 306–342 (2006).

125.  Russo, J. et al. The genomic signature of breast cancer prevention. Recent Results Cancer Res. 174, 131–150 (2007).

126.  Blakely, C. M. et al. Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy. Cancer Res. 66, 6421–6431 (2006).

127.  Russo, J. et al. Comparative study of human and rat mammary tumorigenesis. Lab. Invest. 62, 244–278 (1990).

128.  Zan, Y. et al. Production of knockout rats using ENU mutagenesis and a yeast-based screening assay. Nature Biotech. 21, 645–651 (2003).

129.  Nguyen, D. X. & Massague, J. Genetic determinants of cancer metastasis. Nature Rev. Genet. 8, 341–352 (2007).

130.  Tan, B. T., Park, C. Y., Ailles, L. E. & Weissman, I. L. The cancer stem cell hypothesis: a work in progress. Lab. Invest. 86, 1203–1207 (2006).

131.  Sorlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).

132.  Sorlie, T. et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl Acad. Sci. USA 100, 8418–8423 (2003).

133.  Zhao, H. et al. Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. Mol. Biol. Cell 15, 2523–2536 (2004).

134.  Carey, L. A. et al. The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin. Cancer Res. 13, 2329–2334 (2007).

135.  Al-Hajj, M., Becker, M. W., Wicha, M., Weissman, I. & Clarke, M. F. Therapeutic implications of cancer stem cells. Curr. Opin. Genet. Dev. 14, 43–47 (2004).

136.  Bissell, M. J., Radisky, D. C., Rizki, A., Weaver, V. M. & Petersen, O. W. The organizing principle: microenvironmental influences in the normal and malignant breast. Differentiation 70, 537–546 (2002).

137.  Bissell, M. J. & Labarge, M. A. Context, tissue plasticity, and cancer: are tumor stem cells also regulated by the microenvironment? Cancer Cell 7, 17–23 (2005).

138.  Bissell, M. J., Rizki, A. & Mian, I. S. Tissue architecture: the ultimate regulator of breast epithelial function. Curr. Opin. Cell Biol. 15, 753–762 (2003).

139.  Debnath, J., Muthuswamy, S. K. & Brugge, J. S. Morphogenesis and oncogenesis of MCF-10A mammary epithelial acini grown in three-dimensional basement membrane cultures. Methods 30, 256–268 (2003).

140.  MacDonald, I. C., Groom, A. C. & Chambers, A. F. Cancer spread and micrometastasis development: quantitative approaches for in vivo models. Bioessays 24, 885–893 (2002).

R E V I E W S

nATUrE rEvIEWS | cancer vOlUME 7 | SEpTEMBEr 2007 | 671

© 2007 Nature Publishing Group

141.  Wyckoff, J. B., Jones, J. G., Condeelis, J. S. & Segall, J. E. A critical step in metastasis: in vivo analysis of intravasation at the primary tumor. Cancer Res. 60, 2504–2511 (2000).

142.  Chambers, A. F., Naumov, G. N., Vantyghem, S. A. & Tuck, A. B. Molecular biology of breast cancer metastasis. Clinical implications of experimental studies on metastatic inefficiency. Breast Cancer Res. 2, 400–407 (2000).

AcknowledgementsWe are grateful to C. Perou, C. Kuperwasser, M. Bissell, M. Wicha, J. Chang and M. Lewis for kindly providing pre-prints and sharing their data before publication. We would like to thank C. Allred for contributing the histopathology images and K. Schwertfeger for critical reading of the manu-script. We apologize to authors whose work was omitted owing to space l imitations. Supported in part by

1K99CA127,361-01 awarded to T.V.-G. and CA16,303 awarded to J.M.R.

Competing interests statementThe authors declare no competing financial interests.

DATABASESEntrez Gene: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=geneADAM17 | Brca1 | EGFR | GRB7 | Pten | TGFα | Trp53

FURTHER INFORMATIONJeffrey M. Rosen’s homepage: http://www.bcm.edu/rosenlab/Mayo Clinic web page on breast cancer: http://mayoclinic.com/health/breast-cancer/DS00328

alllinksareacTiveinTheonlinepdf

R E V I E W S

672 | SEpTEMBEr 2007 | vOlUME 7 www.nature.com/reviews/cancer

© 2007 Nature Publishing Group